The past 10 years have witnessed the rapid growth of global mobile cellular traffic demands
due to the popularity of mobile devices. While accurate traffic prediction becomes extremely …

Accurate cellular traffic prediction is challenging due to the complex spatial topology of
cellular network and the dynamic temporal feature of mobile traffic. To overcome these …

Timely and accurate cellular traffic prediction is difficult to achieve due to the complex spatial-
temporal characteristics of cellular traffic. The latest approaches mainly aim to model local …

Machine (deep) learning-enabled accurate traffic modeling and prediction is an
indispensable part for future big data-driven intelligent cellular networks, since it can help …

Cellular traffic prediction plays an important role in network management and resource
utilization. However, due to the high nonlinearity and dynamic spatial-temporal correlation, it …

While traffic modeling and prediction are at the heart of providing high-quality
telecommunication services in cellular networks and attract much attention, they have been …

As many location-based applications provide services for users based on traffic conditions,
an accurate traffic prediction model is very significant, particularly for long-term traffic …

Cellular networks are important for the success of modern communication systems, which
support billions of mobile users and devices. Powered by artificial intelligence techniques …

Forecasting with high accuracy the volume of data traffic that mobile users will consume is
becoming increasingly important for precision traffic engineering, demand-aware network …

With the rapid development of mobile cellular technologies and the increasing popularity of
mobile and Internet of Things (IoT) devices, timely mobile traffic forecasting with high …